## Introduction to Operations Research, Volume 1-- This classic, field-defining text is the market leader in Operations Research -- and it's now updated and expanded to keep professionals a step ahead -- Features 25 new detailed, hands-on case studies added to the end of problem sections -- plus an expanded look at project planning and control with PERT/CPM -- A new, software-packed CD-ROM contains Excel files for examples in related chapters, numerous Excel templates, plus LINDO and LINGO files, along with MPL/CPLEX Software and MPL/CPLEX files, each showing worked-out examples |

### From inside the book

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Page 364

s production scheduling problem , where there was excess

there is excess demand capacity . Consequently , rather than introducing a

dummy destination to " receive " the unused

needed ...

s production scheduling problem , where there was excess

**supply**capacity . Nowthere is excess demand capacity . Consequently , rather than introducing a

dummy destination to " receive " the unused

**supply**capacity , the adjustmentneeded ...

Page 431

the network includes a dummy demand node that receives ( at zero cost ) all the

unused

Interfaces describes how , even back then , microcomputers were being used by

...

the network includes a dummy demand node that receives ( at zero cost ) all the

unused

**supply**capacity at the vendors . The July - August 1987 issue ofInterfaces describes how , even back then , microcomputers were being used by

...

Page 985

economy is that of

management of a multiechelon inventory system one step further by also

considering ...

**Supply**Chain Management Another key concept that has emerged in this globaleconomy is that of

**supply**chain management . This concept pushes themanagement of a multiechelon inventory system one step further by also

considering ...

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### Common terms and phrases

activity additional algorithm alternative amount analysis apply assignment assumed basic variable begin BF solution calculate called changes coefficients column complete Consider constraints Construct corresponding cost CPF solution customers decision demand described determine developed distribution entering equations estimated example expected feasible FIGURE final flow formulation given gives hour identify illustrate increase indicates initial inventory iteration linear programming machine Maximize mean million Minimize month needed node objective function obtained operations optimal optimal solution original parameter path payoff plant player possible presented Prob probability problem procedure profit programming problem queueing respectively resulting shown shows side simplex method solution solve step strategy Table tableau tion transportation unit waiting weeks